工业4.0中的可穿戴传感器:预防与工作相关的肌肉骨骼疾病

Morteza Jalali Alenjareghi, Firdaous Sekkay, Camelia Dadouchi, Samira Keivanpour
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引用次数: 0

摘要

与工作有关的肌肉骨骼疾病(WMSDs)是全球健康和经济挑战,特别是在工业化国家,由于残疾和生产力下降造成的GDP损失高达2%。在工业4.0的推动下,可穿戴传感器为实时人体工程学评估和伤害预防提供了革命性的潜力。本系统综述分析了40项同行评议的研究(2013-2024),以评估惯性测量单元(imu)、肌电(EMG)传感器和压力传感器在减轻WMSD风险方面的应用。研究结果表明,可穿戴技术通过实时反馈增强了工作场所的安全性,降低了人体工程学风险,提高了生产率。尽管取得了很大的进步,但诸如可扩展性、用户舒适度和数据隐私等挑战仍然存在。这篇综述强调了标准化协议、伦理框架以及与机器学习的更深层次集成的必要性,以优化传感器的准确性和可用性。未来的研究方向包括推进人工智能驱动的预测人体工程学,解决隐私问题,以及改进传感器设计以实现广泛的工业应用。本研究提供了可操作的见解,以弥合学术研究与不同工业环境中的实际部署之间的差距。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Wearable sensors in Industry 4.0: Preventing work-related musculoskeletal disorders
Work-related musculoskeletal disorders (WMSDs) are a global health and economic challenge, particularly in industrialized nations, accounting for up to 2 % of GDP losses due to disability and productivity reduction. Wearable sensors, driven by Industry 4.0 advancements, offer transformative potential for real-time ergonomic assessment and injury prevention. This systematic review analyzes 40 peer-reviewed studies (2013–2024) to evaluate the application of inertial measurement units (IMUs), electromyography (EMG) sensors, and pressure sensors in mitigating WMSD risks. Findings demonstrate that wearable technologies enhance workplace safety through real-time feedback, reducing ergonomic risks and improving productivity. Despite promising advancements, challenges such as scalability, user comfort, and data privacy persist. This review emphasizes the need for standardized protocols, ethical frameworks, and deeper integration with machine learning to optimize sensor accuracy and usability. Future research directions include advancing AI-driven predictive ergonomics, addressing privacy concerns, and improving sensor design for widespread industrial adoption. This study provides actionable insights to bridge the gap between academic research and practical deployment in diverse industrial settings.
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